Hi I suggest to combine R & Plink this way:

> R code:
> map2 = read.delim("file2.map", header=F, quote="")
> map1 = read.delim("file1.map", header=F, quote="")
> common.snps = which(map2$V2 %in% map1$V2)
> write.table(map2$V2[common.snps], file="list.snps", sep="\t", col.names=F, row.names=F, quote=F )

and finally

> the Plink commands:
> plink --bfile <file1> --extract list.snps --make-bed --out data1
> plink --bfile <file2> --extract list.snps --make-bed --out data2
> plink --bfile data1 --bmerge data2.bed data2.bim data2.fam --make-bed --out merge

I would do this in R (as you can do this for an infinite number of sets by doing an intersection of the intersection...)

common.snps <- intersect(map1$V2, map2$V2)
write.table(common.snps, file = "common_snps.txt", sep ="\t", col.names = FALSE, row.names = FALSE, quote = FALSE )

Why don't you figure out the common snps between the two datasets using a shell command (awk) or a R one-liner. You can then reduce each of those datasets to the same set of SNPS using the "--extract" option and then merge the datasets. Also, you should check if the two datasets have the same build.

--write-snplist + --extract/--make-bed lets you do this purely with plink, though the other solutions also work.

Why not use plink --merge-mode 1, which would output Consensus calls.

The grep command doesn't work for me: grep -f file1.map file2.map | cut -f2 > common_snps.txt I use this:

sort file1.map file2.map|uniq -d > common_lines.txt
awk '{print $2}' common_lines.txt > common_snps.txt

Then use plink --extract and merge